Difference between revisions of "ALT 2020"

From Openresearch
Jump to: navigation, search
Line 17: Line 17:
 
|Accepted papers=38
 
|Accepted papers=38
 
}}
 
}}
 +
== Topics ==
 +
* Design and analysis of learning algorithms.
 +
* Statistical and computational learning theory.
 +
* Online learning algorithms and theory.
 +
* Optimization methods for learning.
 +
* Unsupervised, semi-supervised and active learning.
 +
* Interactive learning, planning and control, and reinforcement learning.
 +
* Connections of learning with other mathematical fields.
 +
* Artificial neural networks, including deep learning.
 +
* High-dimensional and non-parametric statistics.
 +
* Learning with algebraic or combinatorial structure.
 +
* Bayesian methods in learning.
 +
* Learning with system constraints: e.g. privacy, memory or communication budget.
 +
* Learning from complex data: e.g., networks, time series.
 +
* Interactions with statistical physics.
 +
* Learning in other settings: e.g. social, economic, and game-theoretic.

Revision as of 07:52, 17 April 2020

ALT 2020
31st International Conference on Algorithmic Learning Theory
Event in series ALT
Dates 2020/02/08 (iCal) - 2020/02/11
Homepage: http://alt2020.algorithmiclearningtheory.org/
Location
Location: San Diego, USA
Loading map...

Important dates
Papers: 2019/09/20
Submissions: 2019/09/20
Notification: 2019/11/24
Papers: Submitted 128 / Accepted 38 (29.7 %)
Committees
PC chairs: Aryeh Kontorovich, Gergely Neu
PC members: Yasin Abbasi-Yadkori, Pierre Alquier, Shai Ben-David, Nicolò Cesa-Bianchi, Andrew Cotter, Ilias Diakonikolas
Table of Contents

Contents


Topics

  • Design and analysis of learning algorithms.
  • Statistical and computational learning theory.
  • Online learning algorithms and theory.
  • Optimization methods for learning.
  • Unsupervised, semi-supervised and active learning.
  • Interactive learning, planning and control, and reinforcement learning.
  • Connections of learning with other mathematical fields.
  • Artificial neural networks, including deep learning.
  • High-dimensional and non-parametric statistics.
  • Learning with algebraic or combinatorial structure.
  • Bayesian methods in learning.
  • Learning with system constraints: e.g. privacy, memory or communication budget.
  • Learning from complex data: e.g., networks, time series.
  • Interactions with statistical physics.
  • Learning in other settings: e.g. social, economic, and game-theoretic.
Retrieved from "https://www.openresearch.org/mediawiki/index.php?title=ALT_2020&oldid=221318"
Facts about "ALT 2020"
RDF feed
Acceptance rate29.7 +
Accepted papers38 +
AcronymALT 2020 +
End dateFebruary 11, 2020 +
Event in seriesALT +
Event typeConference +
Has PC memberYasin Abbasi-Yadkori +, Pierre Alquier +, Shai Ben-David +, Nicolò Cesa-Bianchi +, Andrew Cotter + and Ilias Diakonikolas +
Has coordinates32° 43' 3", -117° 9' 46"Latitude: 32.717419444444
Longitude: -117.16277222222 +
Has location citySan Diego +
Has location countryCategory:USA +
Has program chairAryeh Kontorovich + and Gergely Neu +
Homepagehttp://alt2020.algorithmiclearningtheory.org/ +
IsAEvent +
NotificationNovember 24, 2019 +
Ordinal31 +
Paper deadlineSeptember 20, 2019 +
Start dateFebruary 8, 2020 +
Submission deadlineSeptember 20, 2019 +
Submitted papers128 +
Title31st International Conference on Algorithmic Learning Theory +